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A "Gigantic leap" in what way? For all the hype coming off the blog circuit, they don't seem to have made much progress in expanding use cases beyond the "toy for internet dilettantes".
A gigantic leap at least in the way of meaningful improvements "under the hood" between releases, which is what you mentioned in your previous response. If it's still not enough to impress you, fair enough, I'll note to bring heavier goalposts next time.
Okay, you are baiting. Have a normal one.
I'm saying that the advancement from GPTs 2 and 3 to GPT 4 was not the product of substantial changes in design principle or architecture. OpenAI's own press material explains as much. Presumably the same is true for Claude and its predecessors as a cursory examination would seem to indicate that Anthropic is working from a similar (if not the same) core architecture.
In any case, the fundamental issues that limit the use of LLMs in wider real-world applications such as the infamous "Large Libel" problem and more general design choices such as treating "bad" output as preferable to no output remain in place. So long as they do, LLMs will continue to be unsuitable for any task requiring either precision or a singular correct answer over something novel.
There are a lot of situations where a 95% chance at a correct answer and a 5% chance of a horribly wrong one isn't acceptable, but last I checked, we haven't thrown out much of mainstream reporting or academia, despite my many grievances with them. LLMs may not (or may!) have an acceptable middleman to cut out and/or scapegoat for legal liability. Even for matters of law, asking a chatbot to then check if it makes sense to even try to find a Real Expert or ELI5ing a twit is a viable strategy, and one not readily served by Google Search or Reddit unless you like being annoying.
That may not have a business case, but that's a different question.
And yet I would argue that this is why LLMs have (despite the hype) not been able to find a niche outside decent translation software, bad fiction, and worse customer service.
Contra the typical SV rationalist narrative, blue-chip engineering firms and the national security apparatus are not "sleeping on LLMs" so much as LLM are just not up to the task.
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